Instructions to use Maaly/host with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maaly/host with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Maaly/host")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Maaly/host") model = AutoModelForTokenClassification.from_pretrained("Maaly/host", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60822374f06b664263c9fc1e7883693c92444f1438543c756a508fe52c6b0de6
- Size of remote file:
- 431 MB
- SHA256:
- 8d70868ab62d408bf34c81655acf4184714219d5e4dafb6d48a0c73ec9683768
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.